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About CLLab

CLLab works on machine learning, the study that allows computational systems to adaptively
improve their performance with experience accumulated from the data
observed—external examples, feedback of the environment, or other pieces of information.
The importance of machine learning is
rapidly and continuously growing with collaboration opportunities on a
broad spectrum of applications inside and outside of computer science.
In multimedia, machines can learn to construct
semantic structures of digital contents
to help users in their search for the desired scene.
In architecture, machines can learn to effectually
manage computing resources, such as the laptop battery,
based on the working pattern of the owner.
In bioinformatics, machines can learn
to identify cancer genes
and suggest promising medicines.
In e-commerce, machines can learn
the preference of
each individual customer and show
targeted advertisements.

Fundamental machine learning research is driven by the following three major questions (directions):